Launch with Sarah's interview introducing the weekend-profit vs waste problem
To master this skill, we're going to step into the shoes of a data consultant. Our new "client" is the campus café, a bustling hub that has a big problem. They have tons of sales data, but they don't know what it's telling them. Your mission is to use their data to create a plan that will make their business more profitable and efficient. The essential question you must answer is: Given two years of POS data, what inventory and staffing plan will maximize weekend profits without raising waste above 3%?
You are about to learn how to turn raw numbers into a powerful story that can change how a business operates. Let's get started.
Revenue is growing, but Sarah realizes she's flying blind in a competitive market. A client's request for an ROI analysis and a shocking discovery that she's underpriced by 15% forces her to embrace data. See how Sarah transitions from simple reporting to using data analysis as a strategic weapon for pricing, proving value, and winning bigger contracts.
Duration: 2:51
1. What shocking discovery did Sarah make during her competitive analysis?
2. What two big problems did Sarah encounter as her business grew more competitive?
3. According to Sarah, what is data analysis in business?
Think about a time when you or someone you know made assumptions about what people wanted, but the reality was different. Share with a partner:
- What was the situation and what assumptions were made?
- How did you discover the assumptions were wrong?
- What data or evidence would have helped avoid the mistake?
- How does this connect to Sarah's pricing discovery and the café's waste problem?
This is one of the most important lessons in modern business. Gut feelings are great, but data provides the truth. Learning to analyze data is what separates successful entrepreneurs from those who are just guessing. This is the skill that helped Sarah confidently raise her prices, prove her value to clients, and win bigger projects.
Our Unit Challenge:
How can Sarah design a self-auditing ledger that would convince a potential angel investor that she keeps "clean books" from day one? That's exactly what we'll learn to build over the next several lessons.
This is your first step into the world of data analytics. You have the data, you have the challenge, and you have your team. It's time to dig in and see what secrets the numbers are hiding. In the next phase, we'll start cleaning up this messy real-world data to prepare it for analysis—because as you'll learn, real-world data is always messy.